Bibliographic record
Abstract
<p style="margin: 0cm 0cm 12pt; text-align: justify; line-height: 15pt; -ms-text-justify: inter-ideograph;"><span style="font-family: 'Georgia','serif'; mso-bidi-font-size: 10.0pt; mso-bidi-font-family: Georgia;" lang="EN-US"><span style="font-size: small;">With continued development of related technologies, Web 2.0 has become an important site of learning innovation. In particular, social networking sites such as Facebook, which have become popular, have the potential to function as an educational tool enabling peer feedback, interaction, and learning in a social context. Preparing appropriate environments for learners with different needs is essential to learning in general and online learning in particular. Yet, in order to create such learning environments, educators must understand differences in students’ learning styles. Although some research focuses on the effects of individual differences such as age and gender on the use of social networking sites, experimental research related to students’ learning styles is still limited. This study used Kolb’s Learning Style Model to investigate differences in student learning outcomes and satisfaction using mobile Facebook for learning, according to learning style. Results showed that participants with “Assimilating” and “Diverging” learning styles performed better than those with “Accomodating” and “Converging” learning styles did and had higher self-efficacy, observational modelling and habit strength toward learning in mobile Facebook. The paper also makes suggestions for integrating mobile Facebook into class and recommendations for future research.</span></span></p>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".